Mean Average Precision (mAP) is a performance metric used for evaluating machine learning models. It is the most popular metric that is used by benchmark challenges such as PASCAL VOC, COCO, ImageNET ...
YOLOv7 Object Detection Paper Explanation & Inference
What is YOLOv7? YOLOv7 is a single-stage real-time object detector. It was introduced to the YOLO family in July'22. According to the YOLOv7 paper, it is the fastest and most accurate real-time ...
YOLOv4 and Darknet For Pothole Detection
In this blog post, we will be training YOLOv4 object detection model on a pothole detection dataset using the Darknet framework. Before we move further, let’s have an overview of the models that ...
Understanding Multiple Object Tracking using DeepSORT
Surveillance cameras plays an essential role in securing our home or business. These cameras are super affordable. So is setting up a surveillance system. The only difficult and expensive part is the ...
YOLOv5: Expert Guide to Custom Object Detection Training
In this article, we are fine tuning YOLOv5 models for custom object detection training and inference. Introduction The field of deep learning started taking off in 2012. Around that time, it ...
Object Detection using YOLOv5 OpenCV DNN in C++ and Python
You can either love YOLOv5 or despise it. You can't ignore YOLOv5! YOLOv5 has gained much traction, controversy, and appraisals since its first release in 2020. Recently, YOLOv5 extended support ...
